639 research outputs found
Partitioned EDF scheduling on a few types of unrelated multiprocessors
A polynomial-time approximation scheme (PTAS) is derived for the partitioned EDF scheduling of implicit-deadline sporadic task systems upon unrelated multiprocessor platforms that are comprised of a constant number of distinct types of processors. This generalizes earlier results showing the existence of polynomialtime approximation schemes for the partitioned EDF scheduling of implicit-deadline sporadic task systems on (1) identical multiprocessor platforms, and (2) unrelated multiprocessor platforms containing a constant number of processors
Packing Sporadic Real-Time Tasks on Identical Multiprocessor Systems
In real-time systems, in addition to the functional correctness recurrent
tasks must fulfill timing constraints to ensure the correct behavior of the
system. Partitioned scheduling is widely used in real-time systems, i.e., the
tasks are statically assigned onto processors while ensuring that all timing
constraints are met. The decision version of the problem, which is to check
whether the deadline constraints of tasks can be satisfied on a given number of
identical processors, has been known -complete in the strong sense.
Several studies on this problem are based on approximations involving resource
augmentation, i.e., speeding up individual processors. This paper studies
another type of resource augmentation by allocating additional processors, a
topic that has not been explored until recently. We provide polynomial-time
algorithms and analysis, in which the approximation factors are dependent upon
the input instances. Specifically, the factors are related to the maximum ratio
of the period to the relative deadline of a task in the given task set. We also
show that these algorithms unfortunately cannot achieve a constant
approximation factor for general cases. Furthermore, we prove that the problem
does not admit any asymptotic polynomial-time approximation scheme (APTAS)
unless when the task set has constrained deadlines, i.e.,
the relative deadline of a task is no more than the period of the task.Comment: Accepted and to appear in ISAAC 2018, Yi-Lan, Taiwa
Reservation-Based Federated Scheduling for Parallel Real-Time Tasks
This paper considers the scheduling of parallel real-time tasks with
arbitrary-deadlines. Each job of a parallel task is described as a directed
acyclic graph (DAG). In contrast to prior work in this area, where
decomposition-based scheduling algorithms are proposed based on the
DAG-structure and inter-task interference is analyzed as self-suspending
behavior, this paper generalizes the federated scheduling approach. We propose
a reservation-based algorithm, called reservation-based federated scheduling,
that dominates federated scheduling. We provide general constraints for the
design of such systems and prove that reservation-based federated scheduling
has a constant speedup factor with respect to any optimal DAG task scheduler.
Furthermore, the presented algorithm can be used in conjunction with any
scheduler and scheduling analysis suitable for ordinary arbitrary-deadline
sporadic task sets, i.e., without parallelism
ILP-based approaches to partitioning recurrent workloads upon heterogeneous multiprocessors
The problem of partitioning systems of independent constrained-deadline sporadic tasks upon heterogeneous multiprocessor platforms is considered. Several different integer linear program (ILP) formulations of this problem, offering different tradeoffs between effectiveness (as quantified by speedup bound) and running time efficiency, are presented
Optimal virtual cluster-based multiprocessor scheduling
Scheduling of constrained deadline sporadic task systems on multiprocessor platforms is an area which has received much attention in the recent past. It is widely believed that finding an optimal scheduler is hard, and therefore most studies have focused on developing algorithms with good processor utilization bounds. These algorithms can be broadly classified into two categories: partitioned scheduling in which tasks are statically assigned to individual processors, and global scheduling in which each task is allowed to execute on any processor in the platform. In this paper we consider a third, more general, approach called cluster-based scheduling. In this approach each task is statically assigned to a processor cluster, tasks in each cluster are globally scheduled among themselves, and clusters in turn are scheduled on the multiprocessor platform. We develop techniques to support such cluster-based scheduling algorithms, and also consider properties that minimize total processor utilization of individual clusters. In the last part of this paper, we develop new virtual cluster-based scheduling algorithms. For implicit deadline sporadic task systems, we develop an optimal scheduling algorithm that is neither Pfair nor ERfair. We also show that the processor utilization bound of us-edf{m/(2m−1)} can be improved by using virtual clustering. Since neither partitioned nor global strategies dominate over the other, cluster-based scheduling is a natural direction for research towards achieving improved processor utilization bounds
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